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Record W2018988626 · doi:10.1520/jte103313

Optical Measurement of Sand Deformation around a Laterally Loaded Pile

2011· article· en· W2018988626 on OpenAlexaff
Jinyuan Liu, Bingxiang Yuan, Van Thien, Ralph Dimaano

Bibliographic record

VenueJournal of Testing and Evaluation · 2011
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPileDeformation (meteorology)Geotechnical engineeringMaterials scienceComposite materialGeologyStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract A sand displacement field around a laterally loaded pile is measured using an image processing technique called digital image correlation. An optical system consisting of a camera, a loading frame, and a computer is developed to capture soil movement during laterally loading the pile. Two images, before and after a deformation, are used to calculate the soil displacement field. Two kinds of piles are used in the tests: one squared-section pile and the other a circular one. Dry loose sand samples are used to simplify the problem. The displacement and strain fields obtained in this study are similar to the ones reported from the field. A trapezoidal strain wedge is measured in sand in front of the laterally loaded pile. The strain wedge develops from the pile edges. The failure planes form an angle with the horizontal, which varies between approximately two-thirds of the frictional angle of soil for the square pile and three-fourths for the circular pile.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.245
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2011
Admission routes1
Has abstractyes

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